While engineers have had success building tiny, insect-like robots, programming them to behave autonomously like real insects continues to present technical challenges. A group of Cornell engineers has been experimenting with a new type of programming that mimics the way an insect's brain works, which could soon have people wondering if that fly on the wall is actually a fly. The amount of computer processing power needed for a robot to sense a gust of wind, using tiny hair-like metal probes embedded on its wings, adjust its flight accordingly, and plan its path as it attempts to land on a swaying flower would require it to carry a desktop-size computer on its back.
Unlike traditional chips that process combinations of 0s and 1s as binary code, neuromorphic chips process spikes of electrical current that fire in complex combinations, similar to how neurons fire inside a brain. Researchers are developing a new class of event-based sensing and control algorithms that mimic neural activity and can be implemented on neuromorphic chips. Because the chips require significantly less power than traditional processors, they allow engineers to pack more computation into the same payload. They developed an 80-milligram flying RoboBee outfitted with a number of vision, optical flow and motion sensors.